Dispatch or Hold? An Inverse Optimization and Reinforcement Learning Approach for Multiobjective On-Demand Delivery
References
- (2018) Inverse optimization with noisy data. Oper. Res. 66(3):870–892.Link, Google Scholar
- (2022) Deep reinforcement learning for inventory control: A roadmap. Eur. J. Oper. Res. 298(2):401–412.Crossref, Google Scholar
- (2018) Coordinated logistics with a truck and a drone. Management Sci. 64(9):4052–4069.Link, Google Scholar
- (2025) Inverse optimization: Theory and applications. Oper. Res. 73(2):1046–1074.Link, Google Scholar
- (2014) Generalized inverse multiobjective optimization with application to cancer therapy. Oper. Res. 62(3):680–695.Link, Google Scholar
- (2024) Courier dispatch in on-demand delivery. Management Sci. 70(6):3789–3807.Link, Google Scholar
- (2022) Deep Q-learning for same-day delivery with vehicles and drones. Eur. J. Oper. Res. 298(3):939–952.Crossref, Google Scholar
- (2024) Managing the personalized order-holding problem in online retailing. Manufacturing Service Oper. Management 26(1):47–65.Link, Google Scholar
- (2025) A prior and posterior order postponement framework for the on-demand food delivery problem. IEEE Trans. Intelligent Transportation Systems 26(10):14879–14895.Crossref, Google Scholar
- (2021) A collaborative communication-Qmix approach for large-scale networked traffic signal control. Chen Y, Zheng N, Sotelo MA, Barbat S, Li L, eds. Proc. 24th IEEE Internat. Conf. Intelligent Transportation Systems (IEEE, Piscataway, NJ), 3450–3455.Google Scholar
- (2024) Inverse optimization of integer programming games for parameter estimation arising from competitive retail location selection. Eur. J. Oper. Res. 312(3):938–953.Crossref, Google Scholar
- (2015) Ensuring service levels in routing problems with time windows and stochastic travel times. Eur. J. Oper. Res. 240(2):539–550.Crossref, Google Scholar
- (2005) Tree-based batch mode reinforcement learning. J. Machine Learn. Res. 6(18):503–556.Google Scholar
- (2016) Gaussian error linear units (GELUs). Preprint, submitted June 27, https://arxiv.org/abs/1606.08415.Google Scholar
- (2019) Optimal learning for urban delivery fleet allocation. Transportation Sci. 53(3):623–641.Link, Google Scholar
- (2019) Online vehicle routing with neural combinatorial optimization and deep reinforcement learning. IEEE Trans. Intelligent Transportation Systems 20(10):3806–3817.Crossref, Google Scholar
- (2018) The one-dimensional dynamic dispatch waves problem. Transportation Sci. 52(2):402–415.Link, Google Scholar
- (2021) Multi-criteria decision making in dynamic slotting for attended home deliveries. Omega (Westport) 102(C):102305. Google Scholar
- (2020) Offline reinforcement learning: Tutorial, review, and perspectives on open problems. Preprint, submitted May 4, https://arxiv.org/abs/2005.01643.Google Scholar
- (2024) Meituan’s real-time intelligent dispatching algorithms build the world’s largest minute-level delivery network. INFORMS J. Appl. Anal. 54(1):84–101.Link, Google Scholar
- (2023) On-demand delivery from stores: Dynamic dispatching and routing with random demand. Manufacturing Service Oper. Management 25(2):595–612.Link, Google Scholar
- (2021) On-time last-mile delivery: Order assignment with travel-time predictors. Management Sci. 67(7):4095–4119.Link, Google Scholar
- (2024) Multiobjective stochastic optimization: A case of real-time matching in ride-sourcing markets. Manufacturing Service Oper. Management 26(2):500–518.Link, Google Scholar
- (2024) Machine learning for data-driven last-mile delivery optimization. Transportation Sci. 58(1):27–44.Link, Google Scholar
- (2020) Ride-hailing order dispatching at Didi via reinforcement learning. INFORMS J. Appl. Anal. 50(5):272–286.Link, Google Scholar
- (2017) Proximal policy optimization algorithms. Preprint, submitted July 20, https://arxiv.org/abs/1707.06347.Google Scholar
- (2022) Quantile inverse optimization: Improving stability in inverse linear programming. Oper. Res. 70(4):2538–2562.Link, Google Scholar
- (2024) Value enhancement of reinforcement learning via efficient and robust trust region optimization. J. Amer. Statist. Assoc. 119(547):2011–2025.Crossref, Google Scholar
- Statista (2025) Online food delivery: Worldwide. Accessed March 9, 2025, https://www.statista.com/outlook/emo/online-food-delivery/worldwide.Google Scholar
- (2025) Optimal scheduling of shared autonomous electric vehicles with multi-agent reinforcement learning: A MAPPO-based approach. Neurocomputing (Amsterdam) 622(C):129343.Crossref, Google Scholar
- TSL-Meituan (2024) TSL data-driven research challenge. Accessed November 1, 2024, https://connect.informs.org/tsl/tslresources/datachallenge.Google Scholar
- (2021) The restaurant meal delivery problem: Dynamic pickup and delivery with deadlines and random ready times. Transportation Sci. 55(1):75–100.Link, Google Scholar
- (2016) Deep reinforcement learning with double Q-learning. Schuurmans D, Wellman MP, eds. Proc. 30th AAAI Conf. Artificial Intelligence (AAAI Press, Palo Alto, CA), 2094–2100.Google Scholar
- (2023) Better together! The consumer implications of delivery consolidation. Manufacturing Service Oper. Management 25(3):903–920.Link, Google Scholar
- (2009) Cutting plane algorithms for the inverse mixed integer linear programming problem. Oper. Res. Lett. 37(2):114–116.Crossref, Google Scholar
- (2019) Routing and scheduling for a last-mile transportation system. Transportation Sci. 53(1):131–147.Link, Google Scholar
- (2024) Deep reinforcement learning for demand fulfillment in online retail. Internat. J. Production Econom. 269(C):109133.Crossref, Google Scholar
- (2016) Approximating the performance of a “last mile” transportation system. Transportation Sci. 50(2):659–675.Link, Google Scholar
- (2024) Data-driven order fulfillment consolidation for online grocery retailing. INFORMS J. Appl. Anal. 54(3):211–221.Link, Google Scholar
- (2022) Transit planning optimization under ride-hailing competition and traffic congestion. Transportation Sci. 56(3):725–749.Link, Google Scholar
- (2022) Reinforcement learning for logistics and supply chain management: Methodologies, state of the art, and future opportunities. Transportation Res. Part E: Logist. Transportation Rev. 162(C):102712.Crossref, Google Scholar
- (2021) Delay to group in food delivery system: A prediction approach. Huang DS, Jo KH, Li J, Gribova V, Hussain A, eds. Proc. 17th Internat. Conf. Intelligent Comput., Part II, Lecture Notes in Computer Science, vol. 12837 (Springer, Cham, Switzerland), 540–551.Google Scholar
- (2024) Inverse optimization for routing problems. Transportation Sci. 59(2):301–321.Link, Google Scholar

